{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d3790d87b1ef0dca",
   "metadata": {},
   "source": [
    "## LLaVA\n",
    "https://arxiv.org/abs/2304.08485"
   ]
  },
  {
   "attachments": {
    "b5ac5288-dfbb-4ccf-a114-71f6bb0ad78a.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "15b178a5-14f9-4ac9-b4e1-68e50f1a2a3f",
   "metadata": {},
   "source": [
    "![image.png](attachment:b5ac5288-dfbb-4ccf-a114-71f6bb0ad78a.png)"
   ]
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "ExecuteTime": {
     "end_time": "2025-08-22T07:02:39.847906Z",
     "start_time": "2025-08-22T07:02:39.844741Z"
    }
   },
   "source": [
    "data = [\n",
    "    (\"数字5.png\", \"这张图片里有什么<|IMG|>图片里是数字5\"),\n",
    "    (\"数字0.png\", \"描述一下这张图片<|IMG|>这张图片背景是黑色的，中间是一个数字0\"),\n",
    "]"
   ],
   "outputs": [],
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "id": "665f550620e71ec5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:01:48.153617Z",
     "start_time": "2025-08-22T07:01:48.148779Z"
    }
   },
   "source": [
    "import os\n",
    "# 设置环境变量\n",
    "os.environ[\"HF_ENDPOINT\"] = \"https://hf-mirror.com\"\n",
    "os.environ[\"HF_HUB_ENABLE_HF_TRANSFER\"] = \"1\"  # 启用高速下载"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "id": "a844cddd7ce9ec46",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:02:01.646940Z",
     "start_time": "2025-08-22T07:01:50.719643Z"
    }
   },
   "source": [
    "from transformers import ChineseCLIPModel, ChineseCLIPProcessor\n",
    "\n",
    "clip_model_name = \"OFA-Sys/chinese-clip-vit-base-patch16\"\n",
    "clip_model = ChineseCLIPModel.from_pretrained(clip_model_name)\n",
    "clip_processor = ChineseCLIPProcessor.from_pretrained(clip_model_name)"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/dadudu/miniconda3/envs/mini-gpt/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n",
      "Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "id": "fdabd634508af00d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:02:41.664359Z",
     "start_time": "2025-08-22T07:02:41.641431Z"
    }
   },
   "source": [
    "from PIL import Image\n",
    "\n",
    "# 获取图片像素值\n",
    "images = [Image.open(image_path) for image_path, caption in data]\n",
    "image_inputs = clip_processor(images=images, return_tensors=\"pt\")\n",
    "print(image_inputs.pixel_values.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 3, 224, 224])\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:03:34.928464Z",
     "start_time": "2025-08-22T07:03:34.924281Z"
    }
   },
   "cell_type": "code",
   "source": "print(image_inputs.pixel_values[0])",
   "id": "1ebe924be4a2620d",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[[1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303],\n",
      "         [1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303],\n",
      "         [1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303],\n",
      "         ...,\n",
      "         [1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303],\n",
      "         [1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303],\n",
      "         [1.9303, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.9303]],\n",
      "\n",
      "        [[2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749],\n",
      "         [2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749],\n",
      "         [2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749],\n",
      "         ...,\n",
      "         [2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749],\n",
      "         [2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749],\n",
      "         [2.0749, 2.0749, 2.0749,  ..., 2.0749, 2.0749, 2.0749]],\n",
      "\n",
      "        [[2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459],\n",
      "         [2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459],\n",
      "         [2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459],\n",
      "         ...,\n",
      "         [2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459],\n",
      "         [2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459],\n",
      "         [2.1459, 2.1459, 2.1459,  ..., 2.1459, 2.1459, 2.1459]]])\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T06:46:57.132380Z",
     "start_time": "2025-08-22T06:46:57.128223Z"
    }
   },
   "cell_type": "code",
   "source": "print(clip_model.vision_model)",
   "id": "a6207a9198729ed2",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ChineseCLIPVisionTransformer(\n",
      "  (embeddings): ChineseCLIPVisionEmbeddings(\n",
      "    (patch_embedding): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16), bias=False)\n",
      "    (position_embedding): Embedding(197, 768)\n",
      "  )\n",
      "  (pre_layrnorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
      "  (encoder): ChineseCLIPVisionEncoder(\n",
      "    (layers): ModuleList(\n",
      "      (0-11): 12 x ChineseCLIPVisionLayer(\n",
      "        (self_attn): ChineseCLIPVisionAttention(\n",
      "          (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
      "          (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
      "          (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
      "          (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
      "        )\n",
      "        (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
      "        (mlp): ChineseCLIPVisionMLP(\n",
      "          (activation_fn): QuickGELUActivation()\n",
      "          (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
      "          (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
      "        )\n",
      "        (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
      "      )\n",
      "    )\n",
      "  )\n",
      "  (post_layernorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
      ")\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:05:04.504884Z",
     "start_time": "2025-08-22T07:05:04.354047Z"
    }
   },
   "cell_type": "code",
   "source": [
    "result = clip_model.vision_model(image_inputs.pixel_values)\n",
    "print(result.last_hidden_state.shape)\n",
    "print(result.pooler_output.shape)"
   ],
   "id": "f392387d7fef290e",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 197, 768])\n",
      "torch.Size([2, 768])\n"
     ]
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "id": "18616b708dc2b14",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:07:02.821231Z",
     "start_time": "2025-08-22T07:07:02.697585Z"
    }
   },
   "source": [
    "# 获取图片特征向量\n",
    "image_features = clip_model.vision_model(image_inputs.pixel_values).pooler_output\n",
    "print(image_features)\n",
    "print(image_features.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[-0.4894, -1.0844, -0.3489,  ...,  0.5612,  0.8177, -0.4751],\n",
      "        [-0.0511, -0.8929, -0.0720,  ...,  1.1067,  1.2712, -0.9289]],\n",
      "       grad_fn=<NativeLayerNormBackward0>)\n",
      "torch.Size([2, 768])\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "id": "e2068ee0ebddfcc9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:08:21.581294Z",
     "start_time": "2025-08-22T07:08:13.861270Z"
    }
   },
   "source": [
    "from modelscope import AutoModelForCausalLM\n",
    "from modelscope import AutoTokenizer\n",
    "\n",
    "qwen_model_name = \"Qwen/Qwen3-0.6B\"\n",
    "qwen_model = AutoModelForCausalLM.from_pretrained(qwen_model_name)\n",
    "qwen_tokenizer = AutoTokenizer.from_pretrained(qwen_model_name)\n",
    "qwen_tokenizer.pad_token = qwen_tokenizer.eos_token  # 指定 pad token\n",
    "\n",
    "qwen_tokenizer.add_tokens([\"<|IMG|>\"])\n",
    "qwen_model.resize_token_embeddings(len(qwen_tokenizer))"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Model from https://www.modelscope.cn to directory: /Users/dadudu/.cache/modelscope/hub/models/Qwen/Qwen3-0.6B\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-08-22 15:08:15,048 - modelscope - INFO - Target directory already exists, skipping creation.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Model from https://www.modelscope.cn to directory: /Users/dadudu/.cache/modelscope/hub/models/Qwen/Qwen3-0.6B\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-08-22 15:08:19,595 - modelscope - INFO - Target directory already exists, skipping creation.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Embedding(151670, 1024)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "id": "201552f75721b084",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:08:53.560378Z",
     "start_time": "2025-08-22T07:08:53.555072Z"
    }
   },
   "source": [
    "# 获取文本token\n",
    "captions = [caption for image_path, caption in data]\n",
    "text_tokenized = qwen_tokenizer(captions, return_tensors=\"pt\", padding=True, truncation=True, max_length=50)\n",
    "text_input_ids = text_tokenized['input_ids']\n",
    "attention_mask = text_tokenized['attention_mask']\n",
    "\n",
    "print(text_input_ids.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 16])\n"
     ]
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "code",
   "id": "dffc00fc98ca0433",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:10:20.507579Z",
     "start_time": "2025-08-22T07:10:20.503698Z"
    }
   },
   "source": [
    "# 获取文本特征向量\n",
    "text_features = qwen_model.get_input_embeddings()(text_input_ids)\n",
    "print(text_features.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 16, 1024])\n"
     ]
    }
   ],
   "execution_count": 13
  },
  {
   "cell_type": "code",
   "id": "43e3297ee3cf4ac2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:11:40.727613Z",
     "start_time": "2025-08-22T07:11:40.716565Z"
    }
   },
   "source": [
    "# 图片特征向量和文本特征向量不一样，需要对齐，利用一个线性层来进行对齐\n",
    "import torch.nn as nn\n",
    "\n",
    "image_proj = nn.Linear(image_features.shape[1], text_features.shape[2])\n",
    "image_features = image_proj(image_features)\n",
    "print(image_features.shape)\n",
    "print(text_features.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 1024])\n",
      "torch.Size([2, 16, 1024])\n"
     ]
    }
   ],
   "execution_count": 14
  },
  {
   "cell_type": "code",
   "id": "195e167d3b381ef2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:12:57.358061Z",
     "start_time": "2025-08-22T07:12:57.352298Z"
    }
   },
   "source": [
    "# 找出<|IMG|>在text_input_ids中的位置\n",
    "img_token_pos = []\n",
    "\n",
    "img_token_id = qwen_tokenizer.encode(\"<|IMG|>\")[0]\n",
    "for text_input_id in text_input_ids:\n",
    "    for i in range(text_input_id.shape[0]):\n",
    "        if text_input_id[i] == img_token_id:\n",
    "            img_token_pos.append(i)\n",
    "            break\n",
    "\n",
    "print(img_token_pos)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4, 4]\n"
     ]
    }
   ],
   "execution_count": 15
  },
  {
   "cell_type": "code",
   "id": "fd5ac2597c96a27b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:16:25.122738Z",
     "start_time": "2025-08-22T07:16:25.116513Z"
    }
   },
   "source": [
    "# 把图片特征向量插入到文本特征向量中\n",
    "import torch\n",
    "\n",
    "new_text_features_list = []\n",
    "\n",
    "# 遍历每个文本\n",
    "for i, text_feature in enumerate(text_features):\n",
    "    pos = img_token_pos[i]\n",
    "    # text_feature是一个二维向量, torch.Size([17, 1024])\n",
    "    print(text_feature.shape)\n",
    "\n",
    "    # 获取当前文本对应的图片特征向量\n",
    "    image_feature = image_features[i]\n",
    "    print(image_feature.shape)\n",
    "    image_feature = image_feature.unsqueeze(0)\n",
    "    print(image_feature.shape)\n",
    "\n",
    "    # 替换<|IMG|>文本向量为图片特征向量\n",
    "    new_text_feature = torch.cat([text_feature[:pos], image_feature, text_feature[pos + 1:]])\n",
    "    print(new_text_feature.shape)\n",
    "    new_text_features_list.append(new_text_feature)\n",
    "\n",
    "# 将new_text_features_list转成tensor\n",
    "inputs_embeds = torch.stack(new_text_features_list)\n",
    "print(inputs_embeds.shape)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([16, 1024])\n",
      "torch.Size([1024])\n",
      "torch.Size([1, 1024])\n",
      "torch.Size([16, 1024])\n",
      "torch.Size([16, 1024])\n",
      "torch.Size([1024])\n",
      "torch.Size([1, 1024])\n",
      "torch.Size([16, 1024])\n",
      "torch.Size([2, 16, 1024])\n"
     ]
    }
   ],
   "execution_count": 18
  },
  {
   "cell_type": "code",
   "id": "612425523b372d3f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-22T07:21:00.629487Z",
     "start_time": "2025-08-22T07:20:59.842018Z"
    }
   },
   "source": [
    "outputs = qwen_model(\n",
    "    inputs_embeds=inputs_embeds,\n",
    "    attention_mask=attention_mask,\n",
    "    labels=text_input_ids,\n",
    ")\n",
    "loss = outputs.loss\n",
    "print(loss)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(7.6809, grad_fn=<NllLossBackward0>)\n"
     ]
    }
   ],
   "execution_count": 19
  }
 ],
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